diff --git a/pandas/_libs/hashtable_func_helper.pxi.in b/pandas/_libs/hashtable_func_helper.pxi.in
index c63f368dfae43..326ae36c6a12c 100644
--- a/pandas/_libs/hashtable_func_helper.pxi.in
+++ b/pandas/_libs/hashtable_func_helper.pxi.in
@@ -84,7 +84,8 @@ cpdef value_count_{{dtype}}({{c_type}}[:] values, bint dropna):
         int64_t[:] result_counts
         {{endif}}
 
-        Py_ssize_t k
+        # Don't use Py_ssize_t, since table.n_buckets is unsigned
+        khiter_t k
 
     table = kh_init_{{ttype}}()
     {{if dtype == 'object'}}
@@ -132,7 +133,8 @@ def duplicated_{{dtype}}(const {{c_type}}[:] values, object keep='first'):
         {{if dtype != 'object'}}
         {{dtype}}_t value
         {{endif}}
-        Py_ssize_t k, i, n = len(values)
+        Py_ssize_t i, n = len(values)
+        khiter_t k
         kh_{{ttype}}_t *table = kh_init_{{ttype}}()
         ndarray[uint8_t, ndim=1, cast=True] out = np.empty(n, dtype='bool')
 
@@ -222,7 +224,8 @@ def ismember_{{dtype}}(const {{c_type}}[:] arr, {{c_type}}[:] values):
     boolean ndarry len of (arr)
     """
     cdef:
-        Py_ssize_t i, n, k
+        Py_ssize_t i, n
+        khiter_t k
         int ret = 0
         ndarray[uint8_t] result
         {{c_type}} val
@@ -295,7 +298,8 @@ def mode_{{dtype}}({{ctype}}[:] values, bint dropna):
     cdef:
         int count, max_count = 1
         int j = -1  # so you can do +=
-        Py_ssize_t k
+        # Don't use Py_ssize_t, since table.n_buckets is unsigned
+        khiter_t k
         kh_{{table_type}}_t *table
         ndarray[{{ctype}}] modes
 
diff --git a/pandas/_libs/src/parser/tokenizer.c b/pandas/_libs/src/parser/tokenizer.c
index 7ba1a6cd398c9..a195c0daf5271 100644
--- a/pandas/_libs/src/parser/tokenizer.c
+++ b/pandas/_libs/src/parser/tokenizer.c
@@ -709,7 +709,7 @@ int skip_this_line(parser_t *self, int64_t rownum) {
 }
 
 int tokenize_bytes(parser_t *self,
-                   size_t line_limit, int64_t start_lines) {
+                   size_t line_limit, uint64_t start_lines) {
     int64_t i;
     uint64_t slen;
     int should_skip;
@@ -1348,7 +1348,7 @@ int parser_trim_buffers(parser_t *self) {
 
 int _tokenize_helper(parser_t *self, size_t nrows, int all) {
     int status = 0;
-    int64_t start_lines = self->lines;
+    uint64_t start_lines = self->lines;
 
     if (self->state == FINISHED) {
         return 0;
diff --git a/pandas/_libs/tslibs/period.pyx b/pandas/_libs/tslibs/period.pyx
index 9757c4d36d5fa..aadf2c41f7941 100644
--- a/pandas/_libs/tslibs/period.pyx
+++ b/pandas/_libs/tslibs/period.pyx
@@ -76,7 +76,7 @@ from pandas._libs.tslibs.tzconversion cimport tz_convert_utc_to_tzlocal
 
 cdef:
     enum:
-        INT32_MIN = -2_147_483_648
+        INT32_MIN = -2_147_483_648LL
 
 
 ctypedef struct asfreq_info:
@@ -108,9 +108,11 @@ cdef extern from *:
     #define FR_UND -10000    /* Undefined */
 
     // must use npy typedef b/c int64_t is aliased in cython-generated c
+    // unclear why we need LL for that row.
+    // see https://github.com/pandas-dev/pandas/pull/34416/
     static npy_int64 daytime_conversion_factor_matrix[7][7] = {
         {1, 24, 1440, 86400, 86400000, 86400000000, 86400000000000},
-        {0,  1,   60,  3600,  3600000,  3600000000,  3600000000000},
+        {0LL,  1LL,   60LL,  3600LL,  3600000LL,  3600000000LL,  3600000000000LL},
         {0,  0,   1,     60,    60000,    60000000,    60000000000},
         {0,  0,   0,      1,     1000,     1000000,     1000000000},
         {0,  0,   0,      0,        1,        1000,        1000000},